Modelling

The modelling team is responsible for:

1. Verifying that the designed genetic circuit elicits the desired behavior in E coli. A deterministic model of the circuit has been developed in order to predict the dynamical behavior of the circuit in the presence of a concentration gradient of IPTG and various concentrations of Mercury or aTc (anhydrotetracycline).
2. Providing specifications for the quantification device (size, number of bacteria, IPTG gradient). The apparition of the red line indicating the presence and quantity of Mercury or aTc is sensitive to fluctuations in the concentration of these molecules and IPTG. We took into account these fluctuations in a stochastic version of the circuit model, which we have used to determine the specifications of our device.

Table of content

In the following pages, we detail the development of the deterministic and stochastic models, together with their dynamical analysis. Solving numerically these systems required tricky calculations, since they evolve both in time and space. To help future teams with similar calculations, we explain in details the algorithms that were used and provide the scripts here. The modelling results are described in the last section.

For an introduction to the modelling of biological genetic circuit see our tutorials in the human practice section or them here :

• Modelling for biologist
• Synthetic Biology for modellers

Construction of the model :
Establishment of the equation Toggle switchQuorum sensing
Our algorithms


Stochastic Modelling :
Sensitivity to noise: a first approach
Gillespie algorithm
Mean, standard deviation and statistical properties

Parameters
Table of parameters

You can find our modelling results here.

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